New and Exciting in PLoS ONE - articles with embedded interactive 3D structures

There are 19 new articles in PLoS ONE today.

But first, you need to look at the new Collection of articles - Structural Biology and Human Health: Medically Relevant Proteins from the SGC - in which you can see the protein structures in 3D, turn them around, zoom in and out, and do other manipulations of the embedded object, right there inside the articles. Read more about it in: A New Method for Publishing Three-Dimensional Content:

A new method for electronic publishing of articles with text linked to its interactive three dimensional content is described. The method is based on a single document containing a variety of objects such as formatted text, multiple three dimensional molecular objects, textured shapes and surfaces, data tables and graphs, chemical spreadsheets, alignments, etc. The 3D article can then be published for an online web delivery using the activeICM/active X components as well as be downloaded as a single file to be browsed with all its attached objects locally with the ICM browser. Both activeICM and ICM browser are freely available for the public. This method eliminates the need for multiple methods for the web and the local off-line delivery; it offers the dramatically enhanced, customizable and interactive delivery of article's three dimensional content and data attachments in a single compact file.

See the explanation on everyONE blog and the first reactions by Dave Bath, Jean-Claude Bradley and Nick Anthis.

Also today - and as always, you should rate the articles, post notes and comments and send trackbacks when you blog about the papers - here are my own picks for the week:

Influenza A Gradual and Epochal Evolution: Insights from Simple Models:

The recurrence of influenza A epidemics has originally been explained by a "continuous antigenic drift" scenario. Recently, it has been shown that if genetic drift is gradual, the evolution of influenza A main antigen, the haemagglutinin, is punctuated. As a consequence, it has been suggested that influenza A dynamics at the population level should be approximated by a serial model. Here, simple models are used to test whether a serial model requires gradual antigenic drift within groups of strains with the same antigenic properties (antigenic clusters). We compare the effect of status based and history based frameworks and the influence of reduced susceptibility and infectivity assumptions on the transient dynamics of antigenic clusters. Our results reveal that the replacement of a resident antigenic cluster by a mutant cluster, as observed in data, is reproduced only by the status based model integrating the reduced infectivity assumption. This combination of assumptions is useful to overcome the otherwise extremely high model dimensionality of models incorporating many strains, but relies on a biological hypothesis not obviously satisfied. Our findings finally suggest the dynamical importance of gradual antigenic drift even in the presence of punctuated immune escape. A more regular renewal of susceptible pool than the one implemented in a serial model should be part of a minimal theory for influenza at the population level.

Temporal-Difference Reinforcement Learning with Distributed Representations:

Temporal-difference (TD) algorithms have been proposed as models of reinforcement learning (RL). We examine two issues of distributed representation in these TD algorithms: distributed representations of belief and distributed discounting factors. Distributed representation of belief allows the believed state of the world to distribute across sets of equivalent states. Distributed exponential discounting factors produce hyperbolic discounting in the behavior of the agent itself. We examine these issues in the context of a TD RL model in which state-belief is distributed over a set of exponentially-discounting "micro-Agents", each of which has a separate discounting factor (γ). Each µAgent maintains an independent hypothesis about the state of the world, and a separate value-estimate of taking actions within that hypothesized state. The overall agent thus instantiates a flexible representation of an evolving world-state. As with other TD models, the value-error (δ) signal within the model matches dopamine signals recorded from animals in standard conditioning reward-paradigms. The distributed representation of belief provides an explanation for the decrease in dopamine at the conditioned stimulus seen in overtrained animals, for the differences between trace and delay conditioning, and for transient bursts of dopamine seen at movement initiation. Because each µAgent also includes its own exponential discounting factor, the overall agent shows hyperbolic discounting, consistent with behavioral experiments.

Balancing with Vibration: A Prelude for 'Drift and Act' Balance Control:

Stick balancing at the fingertip is a powerful paradigm for the study of the control of human balance. Here we show that the mean stick balancing time is increased by about two-fold when a subject stands on a vibrating platform that produces vertical vibrations at the fingertip (0.001 m, 15-50 Hz). High speed motion capture measurements in three dimensions demonstrate that vibration does not shorten the neural latency for stick balancing or change the distribution of the changes in speed made by the fingertip during stick balancing, but does decrease the amplitude of the fluctuations in the relative positions of the fingertip and the tip of the stick in the horizontal plane, A(x,y). The findings are interpreted in terms of a time-delayed "drift and act" control mechanism in which controlling movements are made only when controlled variables exceed a threshold, i.e. the stick survival time measures the time to cross a threshold. The amplitude of the oscillations produced by this mechanism can be decreased by parametric excitation. It is shown that a plot of the logarithm of the vibration-induced increase in stick balancing skill, a measure of the mean first passage time, versus the standard deviation of the A(x,y) fluctuations, a measure of the distance to the threshold, is linear as expected for the times to cross a threshold in a stochastic dynamical system. These observations suggest that the balanced state represents a complex time-dependent state which is situated in a basin of attraction that is of the same order of size. The fact that vibration amplitude can benefit balance control raises the possibility of minimizing risk of falling through appropriate changes in the design of footwear and roughness of the walking surfaces.